wgblas implements all the standard single-precision level 1, 2, and 3 BLAS routines on top of WebGPU. Next up: double-precision routines, and single- and double-precision complex routines.
- Node.js 22+
npm install wgblasimport { init, cleanup } from "wgblas";
import { sscal } from "wgblas/sscal";
const device = await init();
const n = 5;
const alpha = 3;
const x = new Float32Array([1, 2, 3, 4, 5]);
console.log("before:", x);
const { x: result } = await sscal(device, n, alpha, x, 1);
console.log("after: ", result); // [3, 6, 9, 12, 15]
cleanup();No bundler needed. Load the pre-built browser bundle from the CDN and use window.wgblas directly:
<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<title>sscal — wgblas browser example</title>
<script src="https://unpkg.com/wgblas/dist/wgblas.browser.js"></script>
</head>
<body>
<pre id="out">Running…</pre>
<script>
const { init, sscal, cleanup } = window.wgblas;
(async () => {
const device = await init();
const n = 5;
const alpha = 3;
const x = new Float32Array([1, 2, 3, 4, 5]);
const xBefore = Array.from(x).map(v => v.toFixed(4)).join(", ");
const { x: result } = await sscal(device, n, alpha, x, 1);
document.getElementById("out").textContent =
"before: " + xBefore +
"\nafter: " + Array.from(result).map(v => v.toFixed(4)).join(", ");
cleanup();
})();
</script>
</body>
</html>GpuVector keeps data resident on the GPU between operations — upload once, chain any number of operations, read back once. This eliminates the redundant uploads and readbacks between steps, which are often more expensive than the compute itself.
import { init, cleanup } from "wgblas";
import { saxpy } from "wgblas/saxpy";
import { sscal } from "wgblas/sscal";
import { GpuVector } from "wgblas/classes/GpuVector";
const device = await init();
const n = 5;
const alpha = 2;
const scale = 0.5;
const x = new Float32Array([1, 2, 3, 4, 5]);
const y = new Float32Array([10, 20, 30, 40, 50]);
const xGpu = GpuVector.from(x);
const yGpu = GpuVector.from(y);
console.log("x: ", x);
console.log("y: ", y);
// results stay in the GPU.
await saxpy(device, n, alpha, xGpu, 1, yGpu, 1); // y = 2x + y = [12, 24, 36, 48, 60]
await sscal(device, n, scale, yGpu, 1); // y = 0.5y = [6, 12, 18, 24, 30]
// single readback
const result = await yGpu.read();
console.log("result: ", result); // [6, 12, 18, 24, 30]
xGpu.destroy();
yGpu.destroy();
cleanup();wgblas runs in any browser with WebGPU enabled. Check if it's working in your browser at webgpureport.org.
For full WebGPU control, enable all three flags at chrome://flags and relaunch:
| Flag | What it does |
|---|---|
#enable-unsafe-webgpu |
Enables WebGPU |
#force-enable-webgpu-interop |
Uses the real GPU via Vulkan (Linux) — without this Chrome may fall back to SwiftShader, a CPU-based software renderer |
#enable-webgpu-developer-features |
Unlocks additional GPU features |
You can verify which GPU is being used at webgpureport.org — if the adapter name shows SwiftShader, the real GPU is not being used.
WebGPU must be enabled manually via about:config. Search for each preference and set it:
| Preference | Value | What it does |
|---|---|---|
dom.webgpu.enabled |
true |
Enables WebGPU |
dom.webgpu.wgpu-backend |
vulkan |
Forces the real GPU via Vulkan — without this Firefox may use a software renderer |
gfx.webgpu.ignore-blocklist |
true |
Bypasses the GPU blocklist |
Note: dom.webgpu.wgpu-backend is a string preference — click the pencil icon to edit it and type vulkan.
Restart Firefox after making changes.
Note: Firefox's WebGPU implementation is incomplete and some routines may not work correctly. Chrome is recommended.
Multi-GPU: Firefox only exposes one WebGPU adapter (the display GPU, typically integrated) even on dual-GPU systems — verified via
about:support→ Graphics → WebGPU Default Adapter. Chrome picks the discrete GPU viapowerPreference: "high-performance"; Firefox does not.